To model breakdown voltage using artificial neural networks of solid insulating materials

During manufacture, insulating materials may have voids which are source to electrical trees. Due to partial discharge, the insulating material degrades and breakdown occurs. The factors contributing to the breakdown are difficult to determine. As the equation describing the function is unknown, function estimation, which has some of its own useful properties, a major field of Artificial neural networks, is used. In this project using Artificial Neural Network, we develop models which intakes four different possible inputs that effect the breakdown which are the insulating sample thickness (t), void thickness (t1), void diameter(d) and the materials¡¦ permittivity (ƒÕr) predicts the breakdown voltage as a function of these four inputs. The Neural Network needs to be trained to be able to predict the Breakdown Voltage as close as possible. For the purpose of training , experimental data using a cylinder plane electrode system is used. The different dimensions used will be used to create the voids artificially. The parameters are selected after detail studying of the models as to which would generate best results. After the training is completed, the breakdown voltage as a function of the four input parameters is predicted. The results are very convincing as the error with which it is predicted is very less. Hence, this again proves the capability and effectiveness of using simulation models. MATLAB 2010 is used for doing the simulation process

Filter � GA Based Approach to Feature Selection for Classification

This paper presents a new approach to select reduced number of features in databases. Every database has a given number of features but it is observed that some of these features can be redundant and can be harmful as well as and can confuse the process of classification. The proposed method applies filter attribute measure and binary coded Genetic Algorithm to select a small subset of features. The importance of these features is judged by applying K-nearest neighbor (KNN) method of classification. The best reduced subset of features which has high classification accuracy on given databases is adopted. The classification accuracy obtained by proposed method is compared with that reported recently in publications on twenty eight databases. It is noted that proposed method performs satisfactory on these databases and achieves higher classification accuracy but with smaller number of features

Effect of Yoga and Classical Music on Uterine Artery Indices

During antenatal period, the fetus and mother are connected through placenta, a structure that perform the functions of supplying nutrients to foetus, exchange of gases and elimination of waste through well maintained blood circulation. Thus, foetal health is dependent on this circulation. Any impairment in it can cause adverse effects on foetus. The present case study aimed at understanding the effect of yoga and Indian classical music on maternal and foetal health. Along with routine antenatal care, the patient was advised yoga exercises and listening to some Indian classical music ragas. Today, the effect of yoga and music has been examined on various physical and psychological dimensions of pregnant women. However, there are still sparse studies on the effect of yoga and music on the uterine artery indices as well as maternal and foetal complications. It was found that yoga and classical music resulted in improved uterine artery indices, foeto-maternal health and good foetal outcome

An Effective Prediction Factors for Coronary Heart Disease using Data Mining based Classification Technique

Identification of diseases are very challenging task in field of medical science. Heart disease is very critical issues facing by the people. In our proposed work we have used data mining based classification techniques for analysis and classification of different level of heart disease namely Cleveland, Switzerland, Hungarian and Long Beach. We have used WEKA and Rapid miner data mining tools for analysis of heart disease data set and compared the performance of different classification techniques with four heart disease data set using WEKA and Rapid Miner data mining tool. The proposed SVM gives better accuracy as 66.67% with Hungarian data set in case of WEKA data mining tool while Decision Stump gives better accuracy as 63.94% with same Hungarian data set in case of Rapid miner data mining tool. The Hungarian data set gives better performance with our proposed data mining tools and classification techniques which can help the people to predict effective factors about Coronary Heart Disease

A Review of Particle Swarm Optimization: Feature Selection, Classification and Hybridizations

Particle swarm optimization (PSO) is a recently grown, popular, evolutionary and conceptually simple but efficient algorithm which belongs to swarm intelligence category. This paper outlines basic concepts and reviews PSO based techniques with their applications to classification and feature selection along with some of the hybridized applications of PSO with similar other techniques. DOI: 10.17762/ijritcc2321-8169.16041

ETIOPATHOLOGICAL STUDY OF MOST COMMON DIGESTIVE DISORDER AJIRNA (INDIGESTION)

Ayurveda consider Health and Disease both as the products of food and life style. Today when population is moving with modernization in the 21st century a lot of new diseases emerge out due to faulty life style, improper diet and unhealthy food lack of exercise, mental stress and sleep all are disturbs the biological clock of human being and produce many new life style diseases. Ajirna is the one of the most common disease which is originate from digestive insufficiency (Agni) due to all above factors of modern Era. Ayurveda is the ancient Indian system of medicine, deals with management and prevention of disease. Ayurveda has given prime importance to Agni as it is one of the basic biological elements of the living body.Its own physical characteristics, location and function and secretions like digestive juices and enzymes which participate in the digestive and metabolic functions. Therefore, Ayurveda considers Dehagni as the cause of life, Complexion, Strength, Health, Oja, Teja (energy) and Prana. Ayurveda consider that no disease ever be develop without the derangement of Agni. Ajirna arises as a result of less, excessive and irregular digestion of food and long term of this situation production of Amadosa and circulate all over the body. Further Amadosa combined with other Dosas and Dushyas vitiated them and produce many diseases. Preventive measures like Dincharya, Ratricharya, Ritucharya, Sadvrita and Pathya palana Dasvidhsbhojana Grahan Niyam are the preventive measure for Ajirn in Ayurveda

Effect of storage on composition, physico-chemical, rheology, sensory and microbiological quality of Indian cookie Rava Burfi

In the present study, changes in compositional, physico-chemical, rheological, sensory and microbial properties (SPC, coliform count and yeast and mould count) of rava burfi packed in composite polyethylene terephthalate (PET)/low density polyethylene (LDPE) film was monitored during storage at room temperature (30± 2 °C) and refrigerated temperature (7±2 °C) on every 3 rd for room temperature and on every 7th day for refrigerated temperature of storage till the products became unacceptable. All the changes related to composition, acidity, water activity, Free Fatty Acid (FFA), soluble nitrogen, 5-Hydroxy Methyl Furfural (HMF) and Thiobarbituric Acid (TBA), rheological, sensory and microbiological properties of rava burfi were found to be significantly (P<0.05) affected by storage period (i.e. 9 days at room temperature (30±2 °C) and 35 days at refrigerated (7±2°C) temperat ure). During storage period there was a decrease in moisture content (2.5 to 3.0%) and water activity and an increase in fat, protein, lactose, ash, added sugar, acidity, FFA, soluble nitrogen, TBA and HMF both at ambient (30±2 °C) a s well as at refrigerated (7±2°C) temperature. Changes in rhe ological attributes at both ambient and refrigerated temperatures of storage indicated that there was an increase in hardness, gumminess, chewiness and adhesiveness whereas there was decrease in cohesiveness and springiness values. The sensory scores in terms of flavour, body and texture, colour and appearance and overall acceptability were found to be significantly (P<0.05) decrease with progressive increase in storage period. The shelf life of rava burfi was found to be 9 days at room temperature (30±2 °C) and 35 days at refrigerated (7±2°C) temperature

Extent of Bollworm and Sucking Pest Damage on Modern and Traditional Cotton Species and Potential for Breeding in Organic Cotton

Resistance against cotton bollworm is one of the main arguments for the use of genetically modified (GM) Bt cotton around the globe. The use of GM is prohibited in organic systems and thus the remunerative value of organic cotton cultivation depends on effective bollworm control. In this study, we investigated the extent of bollworm and sucking pest damage in 68 different hybrid and varietal lines of Gossypium hirsutum and varietal lines of G. arboreum at two different locations with contrasting soil fertility and water dynamics. The damage potential of bollworms was assessed from open capsules at two time points. Sucking pests were assessed at three time points using a scoring method. G. arboreum varietal lines and G. hirsutum hybrids were on average significantly more tolerant than G. hirsutum varietal lines to bollworm under fertile and irrigated situations. For sucking pests, the G. arboreum varietal lines were clearly more tolerant than G. hirsutum hybrids and varietal lines. Since, recently, pink bollworm (Pectinophora gossypiella) became resistant against Bt cotton and pressure of sucking pests severely increased, screening of genetic resources and systems-based cotton breeding for bollworm and sucking pest tolerance will improve sustainability of organic and conventional cotton production

EFFECT OF RASONADI KWATH IN THE MANAGEMENT OF RHEUMATOID ARTHRITIS: A REVIEW

Rheumatoid arthritis is a most common persistent inflammatory arthritis of unknown etiology marked by symmetric, peripheral poly arthritis and often result in joint damage and physical disability. Arthritis is always associated with arthralgia. It is 1.0-1.5% with a female to male ratio of 3:1 functional capacity decrease most rapidly at the beginning of disease and the function state of patients in their first year. R.A. Etiology like Immunological factor (HLA-DRB1), Hormonal factor, contraceptives pills, is also associated with a worse disease outcome in R.A. Particularly in genetically predisposed individuals, some environmental antigen trigger, probably a virus, stimulates the production of autoantibodies (IgM rheumatoid factor) against the body, own IgM immunologlobins. This process can become self perpetuating. The prominent feature is the formation of immune complexes. within the joint resulting from tissue damage. These complex activate complement and attract neutrophils. Phagocytosis of immune complexes by neutrophils leads to release of chemical mediators of inflammation. Continued inflammation stimulates the formation of a proliferative synovitis. This hypertrophic granulation tissue is called pannus. This process is responsible for the causing joint erosions. In Ayurveda it is clinically correlated with Aamvata. According to Bhavprakash Beautiful composition is given in Aamvata chikitsa 26th chapter Rasonadi Kwath. Conceptually it is play very effective role because of its Sothhara, Vedna-sthapana, Kapha-vatashamak, Deepan-Pachan, Anuloman, Shoola-prashman, and also Shunthi is Uttam Aama pachak. The aim of this article is to provide a management for RA by Rasonadi Kwath

TL glow curve and kinetic of gamma irradiated quartz collected from Rasmada mines of C.G. basin

Present paper reports the TL glow curve and kinetic parameter of Quartz. The sample of natural quartz collected from Rasmada mines of C.G. basin is irradiated with gamma source. For gamma exposure Co60 gamma source was used and the exposure of 1 hour to 4 hour was given to the sample with dose 0.5kGy to 2 kGy. TL glow for quartz crystal shows the peaks at temperature 242, 256, 250 and 2520C for doses 2kGy to 0.5 kGy respectively. The powder sample shows TL glow peak at 236, 251, 254 and 2530C respectively. The corresponding activation energy and frequency factor is calculated by peak shape method. The activation energy found to be 0.79 eV for powder and 1.26 eV for quartz crystal, frequency factor is found to be 4X108 to 3X1013sec-1. The maximum activation energy is found for quartz crystal with gamma exposure of 2kGy. The sample shows first and second order kinetics. The sample was characterized by XRD. The Induction coupled plasma activated emission spectra (ICP - AES) analysis was done to find out the percentage of elements in the quartz mineral